2021
DOI: 10.5194/acp-21-14493-2021
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Clustering diurnal cycles of day-to-day temperature change to understand their impacts on air quality forecasting in mountain-basin areas

Abstract: Abstract. Air pollution is substantially modulated by meteorological conditions, and especially their diurnal variations may play a key role in air quality evolution. However, the behaviors of temperature diurnal cycles along with the associated atmospheric condition and their effects on air quality in China remain poorly understood. Here, for the first time, we examine the diurnal cycles of day-to-day temperature change and reveal their impacts on winter air quality forecasting in mountain-basin areas. Three … Show more

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Cited by 5 publications
(2 citation statements)
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“…Among the mountainous areas, atmospheric environment in the Sichuan Basin (SCB) is of particular interest in recent years (Yin et al, 2020;Chang et al, 2021;Kong et al, 2021;Wu et al, 2022), due to both its unique bowl-shaped topography and its high levels of air pollution. The SCB is flanked by mountains-that is, bordered to the west by the TP, to the north by the Daba Mountains, to the east by the Wu mountains, and to the south by the Yunnan-Guizhou Plateau, which together serve to shield the basin from external winds and trap air penetrating the basin via large-scale weather disturbances (Zhang et al, 2019;Guo et al, 2022).…”
Section: Introductionmentioning
confidence: 99%
“…Among the mountainous areas, atmospheric environment in the Sichuan Basin (SCB) is of particular interest in recent years (Yin et al, 2020;Chang et al, 2021;Kong et al, 2021;Wu et al, 2022), due to both its unique bowl-shaped topography and its high levels of air pollution. The SCB is flanked by mountains-that is, bordered to the west by the TP, to the north by the Daba Mountains, to the east by the Wu mountains, and to the south by the Yunnan-Guizhou Plateau, which together serve to shield the basin from external winds and trap air penetrating the basin via large-scale weather disturbances (Zhang et al, 2019;Guo et al, 2022).…”
Section: Introductionmentioning
confidence: 99%
“…Clustering methods separate the objects into specific groups, with the goal that all objects assigned to the same cluster have common characteristics, while different clusters have distinct characteristics (Darby, 2005). Those methods have already been widely used in climate and atmospheric research (Barbados et al ., 1995; Cavazos, 2000; Totz et al ., 2017; Kong et al ., 2021). In this study, the fuzzy c ‐means clustering method (Bezdek, 1981) is selected to classify the amplitude and phase series of SAT annual cycle because they are fuzzy to assign to one specific group over some regions.…”
Section: Introductionmentioning
confidence: 99%